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ICML
2009
IEEE
16 years 7 months ago
Deep transfer via second-order Markov logic
Standard inductive learning requires that training and test instances come from the same distribution. Transfer learning seeks to remove this restriction. In shallow transfer, tes...
Jesse Davis, Pedro Domingos
MCS
2009
Springer
16 years 1 months ago
A Study of Semi-supervised Generative Ensembles
Machine Learning can be divided into two schools of thought: generative model learning and discriminative model learning. While the MCS community has been focused mainly on the lat...
Manuela Zanda, Gavin Brown
COLT
2003
Springer
15 years 12 months ago
Maximum Margin Algorithms with Boolean Kernels
Recent work has introduced Boolean kernels with which one can learn linear threshold functions over a feature space containing all conjunctions of length up to k (for any 1 ≤ k ...
Roni Khardon, Rocco A. Servedio
ECIR
2003
Springer
15 years 8 months ago
Representative Sampling for Text Classification Using Support Vector Machines
In order to reduce human efforts, there has been increasing interest in applying active learning for training text classifiers. This paper describes a straightforward active learni...
Zhao Xu, Kai Yu, Volker Tresp, Xiaowei Xu, Jizhi W...
COGSCI
2010
88views more  COGSCI 2010»
15 years 6 months ago
Domain-Creating Constraints
The contributions to this special issue on cognitive development collectively propose ways in which learning involves developing constraints that shape subsequent learning. A lear...
Robert L. Goldstone, David Landy